---
title: Python Packaging
category: product
entity_type: skill
price: $15
canonical: https://forgehouse.ai/skills/python-packaging/
lang: en
hreflang_alt: https://forgehouse.ai/tr/skiller/python-packaging/
last_updated: 2026-06-20
---

# Python Packaging

> Create distributable Python packages with proper project structure, setup.py/pyproject.toml…

Everything needed to turn Python code into a clean, installable, distributable package using modern standards, pyproject.toml as a single source of truth, src-layout structure, wheel and sdist builds, CLI entry points, and publishing to PyPI. It covers the full lifecycle from project scaffolding to automated, secure releases, so your library installs cleanly for everyone and your CLI tools land on the user's PATH on first install.

## Use cases
- Package a Python library for PyPI distribution
- Build a CLI tool with entry points (Click or argparse)
- Write a complete pyproject.toml with metadata and tooling config
- Set up dynamic git-tag-based versioning
- Automate publishing with GitHub Actions and trusted publishing
- Create namespace packages split across repositories

## Benefits
- Ship packages that install fast and reliably with both wheel and sdist
- Catch packaging bugs early by testing the installed package, not the source
- Eliminate credential leaks using OIDC trusted publishing over stored tokens
- Make CLI commands available on PATH automatically the moment users install

## What’s included
- Minimal and full-featured pyproject.toml templates with classifiers, URLs, and tool config
- src vs flat layout guidance plus multi-package and namespace structures
- CLI patterns with Click and argparse wired to [project.scripts] entry points
- Build-and-publish flow: python -m build, twine check, TestPyPI then PyPI
- Dynamic versioning with setuptools-scm and semantic-versioning constraint rules
- GitHub Actions publish workflow, multi-arch wheel builds, and a pre-release checklist

## Who it’s for
Python developers distributing libraries or CLI tools who want modern, reproducible, and secure packaging instead of legacy setup.py guesswork.

## How it runs
From source tree to PyPI release, the skill runs one disciplined pipeline. Every gate exists because skipping it produces a broken install somewhere:
1. Scaffold the src layout (src/my_package/, tests/, pyproject.toml) so tests run against the installed package, not the loose source, which catches missing-file packaging bugs before release
2. Write pyproject.toml as the single source of truth in 4 layers: build-system backend, project metadata with versioned dependency ranges, optional-dependencies groups (dev, docs), and tool config for ruff, mypy and pytest
3. Register CLI entry points under [project.scripts] and plugin hooks under [project.entry-points], then verify with an editable install that the command lands on PATH
4. Build both artifacts with python -m build: a wheel for fast installs and an sdist as the source fallback, using cibuildwheel for platform-specific wheels when C extensions are involved
5. Validate before publishing: twine check on the dist metadata, install the wheel into a clean venv, import the package and run the CLI to prove it actually works outside the dev machine
6. Release through TestPyPI first, then production PyPI via CI with trusted publishing (OIDC instead of stored tokens), tagging the release so setuptools-scm derives the version from git

## FAQ
### I have a legacy setup.py project, does this only apply to new packages?
It works for both. The modern standard is pyproject.toml as the single source of truth, and migrating an existing setup.py project onto the minimal or full-featured templates is a core use case. The src-layout guidance helps restructure older flat projects too.

### How does the publishing flow avoid me leaking a PyPI token?
The GitHub Actions workflow uses OIDC trusted publishing, so no long-lived token is stored in repo secrets at all. The release path also runs python -m build, twine check, and a TestPyPI rehearsal before anything touches real PyPI.

### Will it write the actual library code or my package's tests?
No. It handles the packaging shell: project structure, pyproject.toml, entry points, versioning with setuptools-scm, and the publish pipeline. The functionality inside the package and its test suite are yours to write.

## Price
$15, one-time, no subscription. VAT included.

Related guide: [AI code review and developer workflow](https://forgehouse.ai/guides/ai-code-review/)